Agriculture Activity Ontology : An ontology forcore vocabulary of agriculture activity
Sungmin Joo1 , Seiji Koide2 , Hideaki Takeda1 , Daisuke Horyu3 ,Akane Takezaki3 , and Tomokazu Yoshida3
1

National Institute of Informatics, 2-1-2 Hitotsubashi, Chiyoda-ku, Tokyo, Japan{joo,takeda}@nii.ac.jp
2
Ontolonomy, LLC., 3-76-3-J901, Mutsukawa, Minami-ku, Yokohama, Japankoide@ontolonomy.co.jp
3
National Agriculture and Food Research Organization, 1-31-1, Kannondai,Tsukuba, Ibaraki, Japan{horyu,akane,jones}@affrc.go.jp

Abstract. This paper proposes Agriculture Activity Ontology(AAO) asa basis of the core vocabulary of agricultural activity. Since concepts ofagriculture activities are formed by the various context such as purpose,means, crop, and field, we organize the agriculture activity ontology asa hierarchy of concepts discriminated by various properties such as purpose, means, crop and field. The vocabulary of agricultural activity isthen defined as the subset of the ontology. Since the ontology is consistent, extendable, and capable of some inferences thanks to DescriptionLogics, so the vocabulary inherits these features. It is expected to use in
the data format in the agricultural IT system.
Keywords: ontology, agriculture, agronomic sciences, knowledge representation, core vocabulary, vocabulary management

1Introduction

The various IT systems have been introduced in farm management to realize
better management, i.e., more eﬃcient resource management, finer production
control and better product quality. Now data management is indispensable infarm management. Data in farm management is also used in own purpose but theaggregated data is used for statistics, analysis and prediction for area agriculture.
Data in agricultural IT systems is nonetheless not easy to federate and integrate since the languages to describe data are not unified. Terminology inagriculture such as names of activity, equipment, and crop has not been wellstandardized mainly because agriculture has been local. Some of locality comesfrom diversity of culture and environment and others from the way of business,i.e., farms are small and run independently. But introduction of IT systems
changed the situation; farms can be connected beyond the barrier of individual
farms, regions, and even culture. But un-unified terminology exists as the problem. Without unified terminology, smooth data exchange cannot be enabled. Sostandardization of terminology is the key to enhance agriculture with IT systems.

2We focus on agriculture activity in this paper. Agriculture activity is the mostbasic element of farm management and also the most diﬃcult to standardize since
it is more abstract than other types of terminology like equipment and crop.

2An Existing Resource: AGROVOCAGROVOC[1] is the well-known vocabulary system which has international interoperability and it contains many terms. However, There are some insuﬃcientfeatures in order to use as the core vocabulary. First of all, the relationship between concepts is not clear. Most of narrower/broader relationship is attachedonly by considering the pair-wise relationship. Thus hierarchy by these relationships are not so consistent. This vague relationship between concepts makes theproblem when adding a new term; it is diﬃcult to define the relation with concepts in AGROVOC, i.e., to find the best position to the new term. In addition,
the number of activity names about rice farming, which is important in Asia
including Japan, are insuﬃcient.

3

Overview of AAO

Agriculture Activity Ontology(AAO) is the basis of the core vocabulary of agriculture activity, and it provides semantics for agricultural activity names. Also,
AAO is formalized by Description Logics[2] in order to define and classify theagricultural activities clearly.
The Structuralization of the Agricultural Activities Our strategy tostructuralize agricultural activities is the top-down, i.e, starting from the mostgeneral activity and expanding it to more specific activities. The important criteria for the top-down approach is how we can classify more specific concepts
consistently. We define more specific concepts by specifying attributes and theirvalues. We furthermore define the general rule for specifying attributes.
We start with the top concept Agriculture Activity which denotes all kind ofactivities related on crop and/or fields. Then we break down the concept into
more concrete concepts. When farmers plan or do a certain agricultural activity,the first decision is what for they would take the action, i.e., purpose is the first
attribute to distinguish agriculture activities. After the purpose is well specified,
we use other attributes, i.e., act(type of action), target, place, means, equipment,and season in this order. Crop is also introduced so as to define the activity for aspecific crop. These eight attributes are used to define the concept and to form
the hierarchy of the agricultural activity. For exmaple, Direct seeding in flooded
paddy field can be expressed with DL as follows;Direct seeding in f looded paddy f ield ≡ Agriculture activity⊓∀purpose.seed propagation

3⊓∀act.sow⊓∀target.seed⊓∀crop.rice⊓∀place.paddy f ield

(1)

Polysemic Concepts There are many activities conducted for the multiple
purposes in the agricultural activities. The typical case is Puddling. it is to plow
the bottom of a rice field, but it is also intended to conduct for the purpose ofwater retention, i.e., preventing from the water leak, and for the purpose of landleveling, i.e., flattening the soil.
P uddling ≡ P ulverization⊔Land leveling⊔Activity f or water retention(2)

In our formalization, these concepts are interpreted as polysemic concept
and modelled as disjunction of multiple concepts since none of multiple concepts
are mandatory rather optional. The polysemic concepts defined with multiple
concepts can properly express features for the activities conducted for multiple
attributions in the Agriculture Activity Ontology.
Reasoning by Agriculture Activity Ontology Since the purpose of AAO isto keep the agriculture activity terms consistent and well-organized, placing newterms at the appropriate location in the ontology is mandatory. The main task ofDescription Logics is to compute truth value in subsumption checking. However,it cannot discover subsumers or subsumees for a given subsumee or subsumer
in a given ontological hierarchies. Therefore, we introduced Schank’s algorithm
for Case-Based Reasoning(CBR)[3] into our OWL[4] reasoning engine named
SWCLOS [5]4 , whereby an appropriate position of a given collection of pairs ofattributes and values can be automatically discovered in coherent hierarchies ofconcepts and their attribute values, starting from a given domain top concept
and descending subsuming chains to specific ones.
Web Services based on AAO AAO is hosted on CAVOC(Common Agricultural VOCabulary, www.cavoc.org). CAVOC allows browsing and searching
concepts of AAO. The key feature of CAVOC is that it provides URIs for namesof agriculture activities. In the page, the hierarchical structure is represented inorder to indicate the narrower concept, the broader concept, and the relationshipbetween concepts. Also, the data of AAO can be downloaded in the RDF/Turtle
formats from cavoc.org/aao/. This format is well supported by many semantic
4

SWCLOS is a lisp-based OWL Full processor on top of Common Lisp Object System(CLOS). It is downloadable from https://github.com/SeijiKoide/SWCLOS.

4tools, and it is possible to convert it into other RDF formats if needed. Also,
we provide a SPARQL endpoint for users to explore AAO data using SPARQLqueries.

4Conclusion and Future Work

We provide the Agriculture Activity Ontology(AAO) so as to standardize the vocabulary for agricultural activities. By using the ontology, it is possible to define
concepts of agriculture activities beyond the linguistic diversity of the vocabulary for agricultural activities. The agriculture activity ontology was adopted as
the part of ”the guideline for agriculture activity names for agriculture IT systems” issued by Ministry of Agriculture, Forestry and Fisheries (MAFF), Japan
in 2016, which is one of the achievements of this study[6].
We are now working to extend our idea to other agriculture domains, i.e., thestandardization of vocabulary for agriculture such as the crop, distribution, andagricultural pesticide. Also, international interoperability is next to do. We havealready connections with other activities for agricultural ontologies(for example
Crop Ontology Group5 ). Our research has begun from the purpose of establishing
the core vocabulary for the field of agriculture of Japan, although it can beindependent regardless of language culture so that it can be applied to various
languages and cultures.

Acknowledgement
This work was supported by Council for Science, Technology and Innovation(CSTI), Cross-ministerial Strategic Innovation Promotion Program(SIP), ”Technologies for creating next-generation agriculture, forestry and fisheries”(fundingagency: Bio-oriented Technology Research Advancement Institution, NARO)

References
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https://www.w3.org/TR/owl-guide/
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Proc. Asian Semantic Web Conf. 2006 (ASWC 2006), LNCS(4185) 263-277 Nov,Springer (2006)
6. Ministry of Agriculture, Forestry and Fisheries (MAFF), Japan : the guideline for
agriculture activity names for agriculture IT systems (2016), http://www.kantei.
go.jp/jp/singi/it2/senmon_bunka/shiryo/shiryo04.pdf (in japanese)5

https://sites.google.com/a/cgxchange.org/cropontologycommunity/